Georgia M. Kapitsaki

Bibliometric studies that analyze research publications assist in understanding the research area better and can reveal trends and emerging research topics. In the research area of Software Engineering, previous works have analyzed author and country participation, and citations, but funding sources have been examined only on a very limited level. In this work, our objective is to examine funding sources encountered in Software Engineering publications, observing at the same time trends that appear over the years. We provide a bibliometric data analysis on funding in top Software Engineering journals (TSE, EMSE, TOSEM) and top conference venues (ICSE, ASE, ESEC/FSE, ESEM, EASE, ISSRE) in the years since the first publication in each venue and till 2023. For this analysis, we have collected relevant data from Scopus and have extracted funding sources via a combination of automated and manual analysis. Among the 20,397 publications analyzed, 1,099 different funding bodies were found. Our results show that funding comes mainly from countries that devote a large amount of their budget on R&D activities (United States, China, Canada), although in recent years there is more diversity in country participation. Also funded publications have increased considerably in the last years. Our work can provide the possibility to see how funding on agency and country level is reflected in Software Engineering publications.

The open science paradigm, digitalisation, interdisciplinarity and internationalisation have significantly changed the research process, collaboration, dissemination and impact of scholarly work in the 21 ^st century. Research impact assessment should include new metrics based on Web 2.0 channels suffering from the following issues: data quality (i.e. accuracy, coverage, comprehensiveness), heterogeneity of data sources and APIs and potential manipulation (i.e. metrics gaming). Although the Findable, Accessible, Interoperable and Reusable (FAIR) principles were designed for research data, they can also be applied to research impact metrics to increase their discoverability and reusability. The main aim of this European Cooperation in Science and Technology (COST) Action is to remove barriers for the wider adoption and reusability of metrics, based on Web 2.0 technologies, which are a significant and vital part of research ecosystems. These metrics can serve as the basis for enhanced research impact assessment and, thus, improve recognition of excellence and foster the further development of science and society. Although Scientometrics, based on Web 2.0, is a paradigm that is over 10 years old, it has not yet been widely adopted. Therefore, a plan or roadmap for transition to Scientometrics 2.0 is needed. This should include recommendations for overcoming the challenges associated with new research impact metrics, as well as frameworks for the evaluation of new metrics and data sources. These challenges include the heterogeneity and comprehensiveness of metrics data sources, the varying quality of metrics data, metrics data gaming etc. Due to the multifaceted nature of these challenges, the Action proposes to create synergies between all interested actors: researchers, research software engineers, librarians, representatives of metrics data providers and policy-makers. This article presents an edited version of the original funding proposal submitted to the COST Open Call 2021.

Context: Privacy legislation has impacted the way software systems are developed, prompting practitioners to update their implementations. Specifically, the EU General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have forced the community to focus on users' data privacy. Despite the vast amount of data on developer issues available in GitHub repositories, there is a lack of empirical evidence on the issues developers of Open Source Software discuss to comply with privacy legislation. Method: In this work, we examine such discussions by mining and analyzing 32,820 issues from GitHub repositories. We partially analyzed the dataset automatically to identify law user rights and principles indicated, and manually analyzed a sample of 1,186 issues based on the type of concern addressed. Results: We devised 24 discussion categories placed in six clusters: features/bugs, consent-related, documentation, data storing/sharing, adaptability, and general compliance. Our results show that developers mainly focus on specific user rights from the legislation (right to erasure, right to opt-out, right to access), addressing other rights less frequently, while most discussions concern user consent, user rights functionality, bugs and cookies management. Conclusion: The created taxonomy can help practitioners understand which issues are discussed for law compliance, so that they ensure they address them first in their systems. In addition, the educational community can reshape curricula to better educate future engineers on the privacy law concerns raised, and the research community can identify gaps and areas for improvement to support and accelerate data privacy law compliance.

The proliferation of the Internet of Things (IoT) and the rise of smart cities are revolutionizing how societies operate and urban ecosystems are managed